In this paper, we describe how to call IMSL routines directly from R and Matlab. In general, use of IMSL reduces software production time and costs. Moreover, the technique we describe streamlines the process further by easing the transition from algorithm development to production code. We show how to integrate IMSL with common tools used by applied mathematicians, data scientists,
and advanced algorithm groups.

To keep pace with ever-increasing customer demands on software functionality and time-to-market expectations, software developers have had to evolve the way they develop code to be both faster
and higher quality. As part of this trend, the Waterfall method of software development began to give way in the late 1990s to a more lightweight method of software development: Agile.

This talk from ScicomP 2015 helps you debug numerical simulations better by reviewing best debugging practices for CUDA and OpenACC-accelerated applications and discussing the development of OpenMP-specific tracing and debugging interfaces (including the OMPD interface for performance analysis).

The prototypical Hadoop MapReduce application has at least one Mapper class, one Reducer class, and one driver class. The Mapper class reads the input data and creates intermediate data. The Reducer class accumulates intermediate information and emits a combined result. The Driver class extends the Hadoop class Configured and implements the Hadoop Tool interface, and is used to configure and execute the job.

Regardless of the industry your business operates in, software is likely all around it. Software powers our cars, airplanes, and even the medical devices we rely on to diagnose and treat illness.

Software makes once-impossible things possible and once-difficult things easier. Software helps businesses in the oil and gas industries remove the guesswork and reduce the cost of finding new deposits; it helps patients safely and automatically inject life-saving medications like insulin.

The software we use today is more complex and more connected than ever before. The Chevy Volt electric automobile has 10 million lines of software code, which actually isn’t all that much compared to many new cars (as we’ll see later) but it’s significantly more than the 1.7 million lines of code in the F-22 Raptor fighter aircraft.

Software security, or rather the lack thereof, has become commonplace and an all too frequently recurring story in print and electronic media around the world. Just a single incident, such as the Target breach, which affected over 100 million people and cost Target an estimated $300 million, has the power to propel the subject of security from the world of IT professionals into the conversations of everyday people. Of course, there have been many incidents, pre- and post-Target. TJ Maxx, P.F. Chang’s, JPMorgan Chase, Snapchat, eBay, Home Depot, Staples... the list goes on and on and includes public, private, and government organizations.

While there’s no doubt that open source software (OSS) is here to stay, that doesn’t mean that developers can feel free to use all and any open source software components with no thought to the vulnerabilities and security issues they may introduce into their development projects. The fact is, there’s no such thing as bulletproof, bug-free, automatically license compliant, and easily auditable software. Not in the open source world and not in the commercial off the shelf (COTS) world.

Use of embedded devices is poised for explosive growth. Early adopters in the automotive, appliance, medical device, and consumer electronics industries are expanding the use of software-powered embedded devices, making products with increased intelligence and adding new features all the time. And many other industries are expected to embrace the Internet of Things (IoT), requiring more software to make powerful, smart, and interconnected devices.